Trustworthiness in Social Big Data Incorporating Semantic Analysis, Machine Learning and Distributed Data Processing

This thesis presents several state-of-the-art approaches constructed for the purpose of (i) studying the trustworthiness of users in Online Social Network platforms, (ii) deriving concealed knowledge from their textual content, and (iii) classifying and predicting the domain knowledge of users and their content. The developed approaches are refined through proof-of-concept experiments, several benchmark comparisons, and appropriate and rigorous evaluation metrics to verify and validate their effectiveness and efficiency, and hence, those of the applied frameworks

On the integration of trust with negotiation, argumentation and semantics

Agreement Technologies are needed for autonomous agents to come to mutually acceptable agreements, typically on behalf of humans. These technologies include trust computing, negotiation, argumentation and semantic alignment. In this paper, we identify a number of open questions regarding the integration of computational models and tools for trust computing with negotiation, argumentation and semantic alignment. We consider these questions in general and in the context of applications in open, distributed settings such as the grid and cloud computing. © 2013 Cambridge University Press.This work was partially supported by the Agreement Technology COST action (IC0801). The authors would like to thank for helpful discussions and comments all participants in the panel on >Trust, Argumentation and Semantics> on 16 December 2009, Agia Napa, CyprusPeer Reviewe

Mining Knowledge Bases for Question & Answers Websites

We studied the problem of searching answers for questions on a Question-and-Answer Website from knowledge bases. A number of research efforts had been developed using Stack Overflow data, which is available for the public. Surprisingly, only a few papers tried to improve the search for better answers. Furthermore, current approaches for searching a Question-and-Answer Website are usually limited to the question database, which is usually the website own content. We showed it is feasible to use knowledge bases as sources for answers. We implemented both vector-space and topic-space representations for our datasets and compared these distinct techniques. Finally, we proposed a hybrid ranking approach that took advantage of a machine-learned classifier to incorporate the tag information into the ranking and showed that it was able to improve the retrieval performance

Experiments and Economic Development: Lessons from Field Labs in the Developing World

Along with the traditional primitives of economic development (material preferences, technology, and endowments), there is a growing interest in exploring how psychological and sociological factores (e.g., bounded rationality, norms, or social preferences) also influence economic decisions, the evolution of institutions, and outcomes. Simultaneously, a vast literature has arisen arguing that economic experiments are important tools in identifying and quantifying the role of institutions, socialnorms and preferences on behavior and outcomes. Reflecting on our experience conducting experiments in the field over more than five years, we survey the growing literature at the intersection of these two research areas. Our review has four components. In the introduction we set the stage identifying a set of behavioral factors that seem to be central for understanding growth and economic development./ We then divide the existing literature in two piles: standard experiments conducted in the field and on how to econometrically identify sociological factors in experimental data. We conclude by suggesting topics for future research.experimental economics, behavioral economics, institutions, social preferences, poverty, development

Exploring Government Contractor Experiences Assessing and Reporting Software Development Status

Reports from academic, commercial, and government organizations have documented software-intensive system cost and schedule overruns for decades. These reports have identified lack of management insight into the software development process as one of many contributing factors. Multiple management mechanisms exist. However, these mechanisms do not support the assessment, and subsequent reporting, of software completion status. Additionally, the conceptual framework, based on industry standards, is limited in its relevance to this study due to an emphasis on what is needed while deferring implementation details. The purpose of this phenomenological study was to explore U.S. government contractors\u27 lived experiences of assessing and reporting software completion status with current measurement mechanisms. Twenty program or project managers responded to interview questions targeting positive and challenging experiences with current measurement mechanisms. Qualitative analysis of the experiential data was based on open and axial coding conducted on interview transcripts. Analysis indicated that costly resources are applied to metrics that do not provide the required level of management insight into completion status. These findings have positive social change implications for program managers, project managers, and researchers by documenting the need to develop relevant and cost-efficient status metrics to provide the critical insight required by management to reduce overruns

Three Essays on the Empowerment Role of Information Technology in Healthcare Services

Information technology (IT) is empowering consumers, service providers, and inventor teams with superior services. Various IT innovations are enabling diverse groups of people to search, exchange, and learn from information. In healthcare services, the context of the three essays of this dissertation, information resources are often not equally accessible to consumers, not transparent between patients and physicians, and hard to locate across technological domains that may be relevant to the development of breakthrough innovations. Focusing on empowering roles of IT in healthcare services, I develop a three-essay dissertation to study how IT can enable information access to (i) address health inequalities in developing regions of the world, (ii) strengthen the physician-patient relationship where patient trust in the physician has atrophied, and (iii) energize inventor teams in the development of medical device innovations. Essay 1 examines consumers’ awareness and use of mobile health that can empower consumers to access health advice information. Essay 2 investigates how online health consultation communities can empower physicians to build trust with patients, and gain social and economic advantages in competitive healthcare services. Essay 3 studies the role of digital capabilities to empower inventor teams in medical device companies by converting expertise of inventor teams into broad and deep knowledge capital and expanding knowledge production regarding medical device innovations. I adopt a pluralistic approach to collect data (surveys administered in multiple languages for Essay 1, scraping web data from online communities for Essay 2, and constructing a multisource archival panel dataset for Essay 3) and analyze data (multivariate analysis for Essay 1, multilevel modeling and econometrics for Essay 2 and Essay 3). The essays contribute to our understanding about the acceptance of empowering IT innovations, the empowering role of user-generated content in online communities for providers of credence services, and the empowering role of IT for inventor teams of healthcare innovations

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

Ensuring alignment, which refers to making models behave in accordance with human intentions [1,2], has become a critical task before deploying large language models (LLMs) in real-world applications. For instance, OpenAI devoted six months to iteratively aligning GPT-4 before its release [3]. However, a major challenge faced by practitioners is the lack of clear guidance on evaluating whether LLM outputs align with social norms, values, and regulations. This obstacle hinders systematic iteration and deployment of LLMs. To address this issue, this paper presents a comprehensive survey of key dimensions that are crucial to consider when assessing LLM trustworthiness. The survey covers seven major categories of LLM trustworthiness: reliability, safety, fairness, resistance to misuse, explainability and reasoning, adherence to social norms, and robustness. Each major category is further divided into several sub-categories, resulting in a total of 29 sub-categories. Additionally, a subset of 8 sub-categories is selected for further investigation, where corresponding measurement studies are designed and conducted on several widely-used LLMs. The measurement results indicate that, in general, more aligned models tend to perform better in terms of overall trustworthiness. However, the effectiveness of alignment varies across the different trustworthiness categories considered. This highlights the importance of conducting more fine-grained analyses, testing, and making continuous improvements on LLM alignment. By shedding light on these key dimensions of LLM trustworthiness, this paper aims to provide valuable insights and guidance to practitioners in the field. Understanding and addressing these concerns will be crucial in achieving reliable and ethically sound deployment of LLMs in various applications

The Relationship Between Athletic Development Personality Factors and Decision Making

Ineffective leadership that results from personality defects, ineffective core executive functions, and emotional decision making can lead to destructive actions and executive failures that affect organizational effectiveness. The purpose of this correlational study was to determine if athletic development personality factors correlate with decision making at the executive leadership level. The research questions focused on determining if there was a relationship between athletic development personality factors and decision making. Social exchange theory, social representations theory, and leadership theories comprised the theoretical framework. Participants included 124 executive decision-makers from the United States, the United Kingdom, South Africa, India, and Singapore who completed an online survey measuring self-assessed athletic development personality factors. The data analysis strategy using multiple regression showed that, while each variable was a positive significant predictor of personality factors, the regression approach eliminated redundant predictors from the 5 variable model. The resulting 3 variable model was significant; focus, ethicalness, and leadership found decision making scores to be higher for respondents with highest scores for focus personality (β = .43, p = .001) and ethicalness personality (β = .28, p = .001) and leadership personality (β = .21, p = .001) significantly contributed to the model. Organizational leaders might use the findings of this study on these key personality factors to enhance their knowledge and increase the relationship paths for positive social change by informing leadership development programs and executive training through educational strategies and best practices

THE FACIAL WIDTH-TO-HEIGHT RATIO AND ITS ROLE IN ADVERTISEMENTS AND ASSESSMENTS OF THREAT POTENTIAL

As do many species, humans visually assess the ability and propensity of others to cause trouble or harm (threat potential), although the mechanisms that guide this ability are unknown. One potential mechanism that may underlie advertisements and assessments of threat is the facial width-to-height ratio (face ratio). The overarching goal of this thesis was to test both the ecological validity of the face ratio (i.e., the extent to which it maps onto an individual’s actual threat potential), and its utility in influencing observers’ first impressions of traits related to threat potential. In Chapter 2, I found that men (n = 146) but not women (n = 76) with larger face ratios were more likely to cheat in a lottery for a cash prize than were men with smaller face ratios. In Chapter 3, to better identify the precise social function of the metric, I examined its differential association with two types of threat-related judgements, untrustworthiness and aggressiveness. The face ratio (n of faces = 141) was more strongly linked to observers’ (n = 129) judgements of aggression than to their judgements of trust, although it is possible that this metric advertises threat potential more generally, of which aggression is a best indicator. In Chapter 4 (which extended some preliminary, additional findings from Chapter 3), I found that observers’ (n = 56) judgements of aggression were strongly correlated with the face ratio (n of faces = 25) even when men were bearded, suggesting that this metric could have been operational in our ancestral past when interactions likely involved bearded men. In Chapter 5, I combined effect sizes from experiments conducted from several independent labs and identified significant (albeit weak) associations between the face ratio and actual threat behaviour, and significant (and stronger) associations between the face ratio and judgements of threat potential. Together, this body of work provides initial evidence that the face ratio, and sensitivity to it, may be part of an evolved system designed for advertising and assessing threat in humans, akin to threat assessment systems identified in other species